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» Unsupervised Learning of Image Transformations
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TIP
2002
179views more  TIP 2002»
13 years 9 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
ICMCS
2005
IEEE
152views Multimedia» more  ICMCS 2005»
14 years 3 months ago
Texture-Based Remote-Sensing Image Segmentation
Typically, high-resolution remote sensing (HRRS) images contain a high level noise as well as possess different texture scales. As a result, existing image segmentation approaches...
Dihua Guo, Vijayalakshmi Atluri, Nabil R. Adam
PAMI
2011
13 years 4 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
ALT
2006
Springer
14 years 6 months ago
Unsupervised Slow Subspace-Learning from Stationary Processes
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Andreas Maurer
IJAR
2006
197views more  IJAR 2006»
13 years 9 months ago
Rough fuzzy set based scale space transforms and their use in image analysis
In this paper we present a multi-scale method based on the hybrid notion of rough fuzzy sets, coming from the combination of two models of uncertainty like vagueness by handling r...
Alfredo Petrosino, Giuseppe Salvi